Experimental

PyStatistics/Lists.py

@@ -107,4 +107,57 @@ def StandardDeviation(Data: list[WeightedNumber, Fraction, Decimal, int, float]
 def MeanAbsoluteDeviation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> float:
     Data = __ConvertData(Data)
     mean = Mean(Data)
-    return round((sum([abs(i - mean) for i in Data]) / len(Data)), 2)
+    return sum([abs(i - mean) for i in Data]) / len(Data)
+
+
+
+def AverageIncrease(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> float:
+    Data = __ConvertData(Data)
+    Data = [(Data[i + 1] - Data[i]) for i in range(len(Data) - 1)]
+    return round((sum(Data) / len(Data)), 2)
+
+
+
+def AverageMultiplication(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> float:
+    Data = __ConvertData(Data)
+    Data = [(Data[i + 1] / Data[i]) for i in range(len(Data) - 1)]
+    return round((sum(Data) / len(Data)), 2)
+
+
+
+def AverageIncreaseInterpolation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> list:
+    Data = __ConvertData(Data)
+
+    ai = AverageIncrease(Data) / 2.0
+
+    Data = [[Data[i], Data[i] + ai] for i in range(len(Data))]
+    return [float(i) for e in Data for i in e][:-1]
+
+
+
+def AverageMultiplicationInterpolation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> list:
+    Data = __ConvertData(Data)
+
+    am = AverageMultiplication(Data) / 2.0
+    Data = [[Data[i], Data[i] * am] for i in range(len(Data))]
+    return [round(float(i), 2) for e in Data for i in e][:-1]
+
+
+
+def PointIncreaseInterpolation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> list:
+    Data = __ConvertData(Data) + [0]
+
+    Differences = [((Data[i + 1] - Data[i]) / 2) for i in range(len(Data) - 1)]
+
+    Data = [[Data[i], Data[i] + Differences[i]] for i in range(len(Differences))]
+    return [round(float(i), 2) for e in Data for i in e][:-1]
+
+
+
+def PointMultiplicationInterpolation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> list:
+    Data = __ConvertData(Data) + [0]
+
+    Multipliers = [((Data[i + 1] / Data[i]) / 2) for i in range(len(Data) - 1)]
+
+    Data = [[Data[i], Data[i] * Multipliers[i]] for i in range(len(Multipliers))]
+    return [round(float(i), 2) for e in Data for i in e][:-1]

README.md

@@ -380,6 +380,24 @@ StandardDeviation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tu
 
 MeanAbsoluteDeviation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> float
 # Returns the MAD (mean absolute deviation) (the average distance between each number and the mean) of a given list (or tuple) of numbers.
+
+AverageIncrease(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> float
+# Returns the AI (average increase) (the average amount each value is increased) of a given list (or tuple) of numbers.
+
+AverageMultiplication(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> float
+# Returns the AM (average multiplication) (the average amount each value is multiplied) of a given list (or tuple) of numbers.
+
+AverageIncreaseInterpolation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> list
+# Returns an interpolation (estimating other potential values of a list of numbers) of a given list (or tuple) of numbers by using the AI (average increase) of the list (or tuple).
+
+AverageMultiplicationInterpolation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> list
+# Returns an interpolation (estimating other potential values of a list of numbers) of a given list (or tuple) of numbers by using the AM (average multiplication) of the list (or tuple).
+
+PointIncreaseInterpolation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> list
+# Returns an interpolation (estimating other potential values of a list of numbers) of a given list (or tuple) of numbers by using the mean of each number and the number after.
+
+PointMultiplicationInterpolation(Data: list[WeightedNumber, Fraction, Decimal, int, float] | tuple[WeightedNumber, Fraction, Decimal, int, float]) -> list
+# Returns an interpolation (estimating other potential values of a list of numbers) of a given list (or tuple) of numbers by using the AM (average multiplication) of each number and the number after.
 ```
 ```py
 Data = [43, 321, 912, 213, 213, 9, 34843]
@@ -408,15 +426,6 @@ print(Range(Data))
 
 print(Outliers(Data))
 # Result: [34843]
-
-print(Variance(Data))
-# Result: 170696185.67
-
-print(StandardDeviation(Data))
-# Result: 13065.08
-
-print(MeanAbsoluteDeviation(Data))
-# Result: 8463.14
 ```
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